报告时间：2018年12月24日(星期一) 9:00

报告地点：北校区西大楼III412

报告题目：Remote Sensing Big Data Processing: Multisensor andMultitemporal Earth Observation

报告人：贾秀萍教授，澳大利亚新南威尔士大学

报告摘要：

Information extraction from spatial big data faces challenges in data relevancy analysis and heterogeneous data modeling. Feature selection and feature extraction are critical to enhance the separability between the classes of interest. Another effective means to cope with the problem is to generate new spatial features and incorporate local information. In this talk, feature mining for finding useful features with a given application will be overviewed and discussed. In particularly, the use of Mutual Information and cluster space representation will be analyzed in detail in terms of their capacity in handling a wide range of data types and distributions.

报告人简介：

Xiuping Jia (M’93–SM’03) received the B. Eng. degree from the Beijing University of Posts and Telecommunications, Beijing, China, in Jan, 1982 and the Ph.D. degree in electrical engineering from The University of New South Wales, Australia, in 1996. Since 1988, she has been with the School of Information Technology and Electrical Engineering, The University of New South Wales, Canberra, Australia, where she is currently an Associate Professor. Her research interests include remote sensing, machine learning and spatial data analysis. Dr Jia has more than 200 publications, including over 100 papers in leading technical journals. She is the co-author of the remote sensing textbook titled Remote Sensing Digital Image Analysis [Springer-Verlag, 3rd (1999) and 4th (2006) eds.]. She is a Subject Editor for the Journal of Soils and Sediments and an Associate Editor of the IEEE Transactions on Geoscience and Remote Sensing since 2005.